ArticleBioMed research international2013
Cloud computing for protein-ligand binding site comparison.
Article in BioMed research international, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 23 citations in OpenAlex.
- Scalable Extraction of Big Macromolecular Data in Azure Data Lake Environment.Molecules (Basel, Switzerland) · 2019Article
- Cloud computing-based TagSNP selection algorithm for human genome data.International journal of molecular sciences · 2015Article
- Cloud4Psi: cloud computing for 3D protein structure similarity searching.Bioinformatics (Oxford, England) · 2014Article
- A novel approach for discovering condition-specific correlations of gene expressions within biological pathways by using cloud computing technology.BioMed research international · 2014Article
- Local alignment tool based on Hadoop framework and GPU architecture.BioMed research international · 2014Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The proteome-wide analysis of protein-ligand binding sites and their interactions with ligands is important in structure-based drug design and in understanding ligand cross reactivity and toxicity. The well-known and commonly used software, SMAP, has been designed for 3D ligand binding site comparison and similarity searching of a structural proteome. SMAP can also predict drug side effects and reassign existing drugs to new indications. However, the computing scale of SMAP is limited. We have developed a high availability, high performance system that expands the comparison scale of SMAP. This cloud computing service, called Cloud-PLBS, combines the SMAP and Hadoop frameworks and is deployed on a virtual cloud computing platform. To handle the vast amount of experimental data on protein-ligand binding site pairs, Cloud-PLBS exploits the MapReduce paradigm as a management and parallelizing tool. Cloud-PLBS provides a web portal and scalability through which biologists can address a wide range of computer-intensive questions in biology and drug discovery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.